A unified model for interpretable latent embedding of multi-sample, multi-condition single-cell data
The advent of single-cell technologies has allowed us not only to generate comprehensive atlases of cell types in their 'normal' states, but also to understand how these cells change under various conditions. Here, we introduce GEDI, a framework to enable the analysis of these datasets.
